Vlastimil Sulc

This study aimed to evaluate the ability of selected microRNAs as biomarkers of atrial fibrillation (AF) in ischemic stroke patients in comparison with other established biochemical biomarkers. A prospective case–control study of consecutive ischemic stroke patients with AF admitted to a comprehensive stroke center was conducted. The control group consisted of patients with ischemic stroke with no AF detected on prolonged (at least 3 weeks) Holter ECG monitoring. As potential biomarkers of AF, we analyzed the plasma levels of microRNAs (miR-21, miR-29b, miR-133b, miR-142-5p, miR-150, miR-499, and miR-223-3p) and 13 biochemical biomarkers at admission. The predictive accuracy of biomarkers was assessed by calculating the area under the receiver operating characteristic curve. The data of 117 patients were analyzed (61 with AF, 56 with no AF, 46% men, median age 73 years, median National Institutes of Health Stroke Scale 6). Biochemical biomarkers (N-terminal pro-B-type natriuretic peptide [NT-proBNP], high-sensitivity cardiac troponin I, fibrinogen, C-reactive protein, eGFR, and total triglycerides) were significantly associated with AF. NT-proBNP had the best diagnostic performance for AF with area under the receiver operating characteristic curve 0.92 (95%, CI 0.86–0.98); a cutoff value of >528 ng/L had a sensitivity of 79% and a specificity of 97%. None of the other biomarkers, including microRNAs, was associated with AF. Conventional biochemical biomarkers (NT-proBNP, high-sensitivity cardiac troponin I, fibrinogen, C-reactive protein, eGFR, and triglycerides), but not microRNAs (miR-21, miR-29b, miR-133b, miR-142-5p, miR-150, miR-499, and miR-223-3p) were significantly associated with AF in our ischemic stroke cohort.

Background: We hypothesized that right and left temporal lobe epilepsy (RTLE and LTLE, respectively) have distinctive spatial patterns of white matter (WM) changes that can be differentiated and interpreted with the use of multiple diffusion parameters. We compared the global microstructure of fiber bundles with regard to WM alterations in both RTLE and LTLE, addressing some of the methodological issues of previous studies. Methods: Diffusion tensor imaging data from 17 patients with RTLE (age: 40.7 ± 10.4), 15 patients with LTLE (age: 37.3 ± 10.4), and 15 controls (age: 34.8 ± 11.2) were used in the study. WM integrity was quantified by fractional anisotropy (FA), mean diffusivity (MD), longitudinal diffusivity (LD), and radial diffusivity (RD). The diffusion parameters were compared between the groups in tracts representing the core of the fiber bundles. The volumes of hippocampi and amygdala were subsequently compared across the groups, while the data were adjusted for the effect of hippocampal sclerosis. Results: Significantly reduced FA and increased MD, LD, and RD were found bilaterally over widespread brain regions in RTLE. An increase in MD and RD values was observed in widespread WM fiber bundles ipsilaterally in LTLE, largely overlapping with regions where FA was lower, while no increase in LD was observed. We also found a difference between the LTLE and RTLE groups for the right hippocampal volume (with and without adjustment for HS), whereas no significant volume differences were found between patients and controls. Conclusions: It appears that patients with RTLE exhibit a more widespread pattern of WM alterations that extend far beyond the temporal lobe in both ipsilateral and contralateral hemisphere; furthermore, these changes seem to reflect more severe damage related to chronic degeneration. Conversely, more restrained changes in the LTLE may imply a pattern of less severe axonal damage, more restricted to ipsilateral hemisphere. Comprehensive finding of more prominent hippocampal atrophy in the RTLE raises an interesting issue of seizure-induced implications on gray matter and WM microstructure that may not necessarily mean a straightforward causal relationship. Further correlations of diffusion-derived metrics with neuropsychological and functional imaging measures may provide complementary information on underlying WM abnormalities with regard to functional hemispheric specialization.

Epilepsy is a prevalent and serious neurological disorder. This vital textbook addresses the role of neuroimaging as a unique tool to provide in vivo biomarkers aimed at furthering our understanding of causes and consequences of epilepsy in a day-to-day clinical context. Unique in its approach, this translational book presents a critical appraisal of advanced pre-clinical biomarkers that allows capturing epileptogenesis at molecular, cellular, and neuronal system levels. The book is divided into four sections. Part I includes a series of chapters focused on imaging of early disease stages. Part II discusses lesion detection and network analysis methods. Part III focuses on imaging methods used to predict response to antiepileptic drugs and surgery. Finally, Part IV presents imaging techniques used to evaluate disease consequence.

MRI-Negative Epilepsy - March 2015

The establishment of memories involves reactivation of waking neuronal activity patterns and strengthening of associated neural circuits during slow-wave sleep (SWS), a process known as “cellular consolidation” (Dudai and Morris, 2013). Reactivation of neural activity patterns during waking behaviors that occurs on a timescale of seconds to minutes is thought to constitute memory recall (O'Keefe and Nadel, 1978), whereas consolidation of memory traces may be revealed and served by correlated firing (reactivation) that appears during sleep under conditions suitable for synaptic modification (Buhry et al., 2011). Although reactivation has been observed in human neuronal recordings (Gelbard-Sagiv et al., 2008; Miller et al., 2013), reactivation during sleep has not, likely because data are difficult to obtain and the effect is subtle. Seizures, however, provide intense and synchronous, yet sparse activation (Bower et al., 2012) that could produce a stronger consolidation effect if seizures activate learning-related mechanisms similar to those activated by learned tasks. Continuous wide-bandwidth recordings from patients undergoing intracranial monitoring for drug-resistant epilepsy revealed reactivation of seizure-related neuronal activity during subsequent SWS, but not wakefulness. Those neuronal assemblies that were most strongly activated during seizures showed the largest correlation changes, suggesting that consolidation selectively strengthened neuronal circuits activated by seizures. These results suggest that seizures “hijack” physiological learning mechanisms and also suggest a novel epilepsy therapy targeting neuronal dynamics during post-seizure sleep.

High frequency oscillations are associated with normal brain function, but also increasingly recognized as potential biomarkers of the epileptogenic brain. Their role in human cognition has been predominantly studied in classical gamma frequencies (30–100 Hz), which reflect neuronal network coordination involved in attention, learning and memory. Invasive brain recordings in animals and humans demonstrate that physiological oscillations extend beyond the gamma frequency range, but their function in human cognitive processing has not been fully elucidated. Here we investigate high frequency oscillations spanning the high gamma (50–125 Hz), ripple (125–250 Hz) and fast ripple (250–500 Hz) frequency bands using intracranial recordings from 12 patients (five males and seven females, age 21–63 years) during memory encoding and recall of a series of affectively charged images. Presentation of the images induced high frequency oscillations in all three studied bands within the primary visual, limbic and higher order cortical regions in a sequence consistent with the visual processing stream. These induced oscillations were detected on individual electrodes localized in the amygdala, hippocampus and specific neocortical areas, revealing discrete oscillations of characteristic frequency, duration and latency from image presentation. Memory encoding and recall significantly modulated the number of induced high gamma, ripple and fast ripple detections in the studied structures, which was greater in the primary sensory areas during the encoding (Wilcoxon rank sum test, P = 0.002) and in the higher-order cortical association areas during the recall (Wilcoxon rank sum test, P = 0.001) of memorized images. Furthermore, the induced high gamma, ripple and fast ripple responses discriminated the encoded and the affectively charged images. In summary, our results show that high frequency oscillations, spanning a wide range of frequencies, are associated with memory processing and generated along distributed cortical and limbic brain regions. These findings support an important role for fast network synchronization in human cognition and extend our understanding of normal physiological brain activity during memory processing.

Quiz Ref ID The prognosis for surgery in magnetic resonance imaging (MRI)–negative temporal lobe epilepsy (TLE) is less favorable than lesional epilepsy. Previous studies demonstrate a favorable postoperative outcome in 36% to 76% of patients with MRI-negative TLE.^1-8 Many factors have been associated with a favorable outcome in MRI-negative TLE,^1,4,9-11 but there has been little improvement in postoperative outcomes.^12,13 Both scalp and intracranial electroencephalography (EEG) play an important role in the selection of surgical candidates. While unilateral or localized ictal onset on scalp EEG has been associated with good outcomes,^11,14 the role of interictal epileptiform discharges (IEDs) in outcomes is less clear.